doi:10.1017/psrm.2017.42> demonstrate that cluster adjusted t statistics (CATs) are an effective method for correcting standard errors in scenarios with a small number of clusters. The 'mmiCATs' package offers a suite of tools for working with CATs. The mmiCATs() function initiates a 'shiny' web application, facilitating the analysis of data utilizing CATs, as implemented in the cluster.im.glm() function from the 'clusterSEs' package. Additionally, the pwr_func_lmer() function is designed to simplify the process of conducting simulations to compare mixed effects models with CATs models. For educational purposes, the CloseCATs() function launches a 'shiny' application card game, aimed at enhancing users' understanding of the conditions under which CATs should be preferred over random intercept models.">

mmiCATs: Cluster Adjusted t Statistic Applications (original) (raw)

Simulation results detailed in Esarey and Menger (2019) <doi:10.1017/psrm.2017.42> demonstrate that cluster adjusted t statistics (CATs) are an effective method for correcting standard errors in scenarios with a small number of clusters. The 'mmiCATs' package offers a suite of tools for working with CATs. The mmiCATs() function initiates a 'shiny' web application, facilitating the analysis of data utilizing CATs, as implemented in the cluster.im.glm() function from the 'clusterSEs' package. Additionally, the pwr_func_lmer() function is designed to simplify the process of conducting simulations to compare mixed effects models with CATs models. For educational purposes, the CloseCATs() function launches a 'shiny' application card game, aimed at enhancing users' understanding of the conditions under which CATs should be preferred over random intercept models.

Version: 0.2.0
Imports: broom, broom.mixed, clusterSEs, DT, lmerTest, MASS, mmcards, pool, robust, robustbase, RPostgres, shiny, shinythemes
Suggests: testthat (≥ 3.0.0)
Published: 2024-08-26
DOI: 10.32614/CRAN.package.mmiCATs
Author: Mackson Ncube [aut, cre], mightymetrika, LLC [cph, fnd]
Maintainer: Mackson Ncube <macksonncube.stats at gmail.com>
BugReports: https://github.com/mightymetrika/mmiCATs/issues
License: MIT + file
URL: https://github.com/mightymetrika/mmiCATs
NeedsCompilation: no
Materials: README
CRAN checks: mmiCATs results

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